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Second, we improve the logistics of emergency interventions, as shown by the two database icons in the lower right corner.
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That could explain the difference in the numbers of articles recovered by the two databases.
As just described, much of the data captured by the two databases is complementary.
Similarly, many of the observed inconsistencies can be ascribed to the different approaches to protein classification adopted by the two databases.
A detailed summary of site-modification combinations not covered by the two databases is presented in Additional file 1: Table S4.
Since boundaries of a domain region annotated by the three database searches were not identical, we used the consensus of all significant domains predictions.
This problem is clearly illustrated by comparing the predictions generated by using the two databases, with the greater number of predicted associations found using the CTD, which includes less-certain, indirect evidence.
To do so, the annotations must be 'dereferenced' by querying the two databases via their web service interfaces.
Children born into DIN in these later years had records of comparable length and composition to children born in during 1989 93, suggesting no appreciable bias was incurred by comparing the two databases outright in the analyses.
Any inconsistency found by CICAMS between the two databases was reported to the local clerks for adjudication until the databases agreed.
Reliability was ensured by the consistency of the two databases.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com